Personalized Pricing and Quality Design
|Keywords:||Competitive strategy;Personalized marketing;Non-linear pricing;Price discrimination;Quality design|
|Publisher:||Stern School of Business, New York University|
|Abstract:||We develop an analytical framework to investigate the competitive implications of personalized pricing and quality allocation (PPQ), whereby firms charge different prices and offer different qualities to different consumers, based on their willingness to pay. We embed PPQ in a model of spatial differentiation, and show how information about consumer preferences affects multi-product firmsÃÂÃÂ¢ÃÂÃÂÃÂÃÂ choices over pricing schedules and product line offerings. We show that firmsÃÂÃÂ¢ÃÂÃÂÃÂÃÂ optimal pricing strategies with PPQ will be non-monotonic in consumer valuations. Our model sheds light on the different product quality schedules offered by firms, given that one or both firms implement PPQ. Contrary to prior literature on one-to-one marketing, we show that even symmetric firms can avoid the well-known PrisonerÃÂÃÂ¢ÃÂÃÂÃÂÃÂs Dilemma problem due to the quality enhancement effect at the individual consumer level. The rent extraction effect due to quality enhancement dominates the adverse effect of price competition. Moreover, this result is stronger when firms have a larger proportion of loyal consumers. When both firms have PPQ, consumer surplus is non-monotonic in valuations such that some low valuation consumers get higher surplus than high valuation consumers. For a wide range of fixed costs, we also demonstrate some results on the profitability of adopting PPQ and show the emergence of asymmetric equilibria, where one firm adopts PPQ and the other firm does not when the number of loyal customers is less than a critical value. We extend our analysis to asymmetric firms and show that when one firm adopts PPQ, it always increases its quality level while the other firm keeps its quality schedule unchanged compared to when neither firm has PPQ. We demonstrate that a firm with an ex-ante, smaller loyal segment can be better off with PPQ.|
|Appears in Collections:||CeDER Working Papers|
IOMS: Information Systems Working Papers
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